Cloud poster availability – optional
The Corresponding Authors are invited to upload their poster in pdf format (max 6 Mb) to a shared, read-only cloud folder where all the participants will be able to view them. Please note that a personal Google account is required for upload.
POSTER COMMUNICATIONS
3.06
Lipid–hormone crosstalk mediated by WRKY125 and LOX4 enhances resistance to Fusarium verticillioides in maize
Lanubile A., Ottaviani L., Lefeuvre R., Montes E., Giorni P., Dall’Asta C., Mithöfer A., Widiez T., Marocco A.
3.07
Hairy root-based screening of CRISPR/Cas9-mediated PSY1 knockout efficiency in Solanum lycopersicum
Grotto F., Nicolia A., Albertini E.
3.08
New cisgenic lines improved for durable resistance against multiple pathogens are available in durum wheat
Mores A., Mastrangelo A.M., Borrelli G.M., Pecchioni N., Giove S.L., Gadaleta A., De Simone V., Giovanniello V., Marone D.
3.09
Unraveling pseudogamous apomixis and facultative parthenogenesis in tetraploid sunflower: from phenotypic characterization to dihaploid production
Bocchini M., Romero G., Pessino S., Amato L., Nestares G., Bianchi M., Marconi G., Albertini E., Ochogavía A.
3.10
From high-density genomic data to minimal discriminatory SNP panels – the SNPoptimizer tool
Esposito S., Scalzi N., Palombieri S., Sanseverino W., Sestili F., Stella A., Balestrini R., Grillo S., Bressan R.A., Batelli G.
3.11
Integrating genomic prediction and crop simulation models to support breeding decisions in Mozambique
Takele Miteku R., Zewdu Tegegn E., Sellitti S., Dell’Acqua M., Caproni L.
3.12
Elucidating the genetic architecture of Xylella fastidiosa resistance in olive via GBS-based mapping
Procino S., Mangini G., Fanelli V., Savoia M.A., Susca L., Montilon V., Venerito P., Nigro F., D’Agostino N., Montemurro C., Taranto F.
3.13
Temporal trajectories of soil microbial diversity and predicted metabolic potential during the first stages of agroforestry establishment in a Mediterranean system
Vettori C., Rubini A., Campagni C., Ferrante R., Paolieri M., Riccioni C., Belfiori B., Paffetti D.
3.14
Sunlight, smartphones, and computer vision: scalable classification of the obscuravenosa phenotype in tomato
Polilli W., Galieni A., Leteo F., Caioni M., Beretta M., Sestili S.
3.15
Deep learning-assisted phenotyping of Septoria tritici blotch symptoms enables genetic dissection of seedling-stage resistance in Triticum turgidum ssps germplasm
Zhou C., Atsbeha Fiseha G., Guo S., Gao T., Cappelletti E., Bozzoli M., Gadaleta A., Mazzucotelli E., Tuberosa R., Prodi A., Salvi S., Maccaferri M.
3.16
Deep learning-based image analysis for estimating plant organ quantitative traits
Guo S., Li X., Salvi S.
3.17
A virus-Induced genome editing system for durum wheat based on stable Cas9 editor plants and BSMV-mediated gRNA delivery
Camerlengo F., Calzini L., Viviani A., Tassinari A., Zitong Y., Akhunov E., Tuberosa R., Salvi S., Maccaferri M.
3.18
Identification of QTLs controlling brown rot resistance and fruit quality traits in F2 peach mapping populations
da Silva Linge C., Mantilla J., Hassan Mustafa M., Baccichet I., Tagliabue A.G., Chiozzotto R., Calastri E., Bassi D., Rossini L., Cirilli M.
3.19
Ultra fast forward identification of candidate variants underlying pale green phenotypes in mutagenized barley populations
Horner D.S., Presello A., Tadini L., Toricella V., Rossini L., Salvi S., Pesaresi P.
3.20
Development and application of a genomic selection pipeline in tomato
Ul-Haq M.A., Francia E., Fricano A., Cattivelli L., Ferrari G., Beretta M.
3.21
Efficient pyramiding of barley mutations to boost biomass and grain yield
Tondelli A., Marè C., Pasquariello M., Palma D., Crosatti C., Rossini L., Pesaresi P., Cattivelli L.